Abstract. Predictive analysis aims at detecting concurrency errors during runtime by monitoring a concrete execution trace of a concurrent program. In recent years, various models ...
Chao Wang, Sudipta Kundu, Malay K. Ganai, Aarti Gu...
Partially Observable Markov Decision Processes have been studied widely as a model for decision making under uncertainty, and a number of methods have been developed to find the s...
A central goal of robotics and AI is to be able to deploy an agent to act autonomously in the real world over an extended period of time. It is commonly asserted that in order to ...
This paper is about Reinforcement Learning (RL) applied to online parameter tuning in Stochastic Local Search (SLS) methods. In particular a novel application of RL is considered i...
We propose a new model for unsupervised POS tagging based on linguistic distinctions between open and closed-class items. Exploiting notions from current linguistic theory, the sy...